Engine combustion may generate particulate matter (PM) and pollutants such as soot and aerosols that can be exhausted to the atmosphere. Various technologies have been developed for filtering such PMs before the exhaust is released to the atmosphere. As an example, to improve emissions compliance, particulate filters (PFs) may be included in the engine exhaust system. One or more PM sensors (also known as soot sensors) may be located upstream and/or downstream of a particulate filter (PF), and may be used to sense PM loading on the filter, schedule regeneration of the filter, and/or diagnose the functionality of the filter.
When included, PM sensors may be used to sense concentration and/or flux of PM entrained in the exhaust gas based on a correlation between a measured change in electrical current and/or conductance at a sensor element and the amount of PM deposited on the element (such as between a pair of measuring electrodes). As such, PM sensors need to be periodically regenerated and reset once the soot accumulation signal strength reaches a threshold value. The time required for a sensor signal to reach the threshold value after which the sensor may be regenerated and reset is known as the response time of the sensor. This response time is inversely proportional to the PM concentration in the exhaust gas. In order to meet emissions regulations, PM sensors are required to be intermittently regenerated and reset (e.g., at least once within each emission test cycle). In addition, to meet emission standards, it may be desirable for an engine controller to have collected a maximum number of sensor response time signals per drive cycle (e.g., at least 4 per 18 mins for a federal test procedure cycle).
One example approach shown by Min Sun in U.S. Pat. No. 9,032,719 discloses a method to reset a PM sensor based on soot accumulation. Therein, PM sensor current may increase with the deposition of soot on the sensor. After a period of time (known as the response time for the sensor), the PM sensor current may reaches a threshold value correlating with the soot load on the sensor reaching a threshold load. At this time, the PM sensor is regenerated and reset.
However, the inventors have recognized that PM sensors may be prone to contamination from impingement of larger particulates present in the exhaust gases and/or water droplets, thus affecting the PM sensor sensitivity and leading to errors in electrical current measurement and PM sensor regeneration. Such erroneous data may not reflect the actual soot concentration in the exhaust gas and hence should not be utilized for determination of sensor response time and particulate filter efficiency. Due to repeated occurrence of noise, a large amount of data may not be utilized for PM sensor operation and is required to be discarded. In the absence of an actual response time, the soot concentration calculation from an average response time may have reduced accuracy. For short drives, there may be not be sufficient measurement of soot concentration due to the lack of time in the given drive cycle. As such, this reduces the accuracy of the soot monitoring system. For example, for a soot sensor downstream of the particulate filter, if the average response time is higher than the actual response time, soot will be underestimated thereby potentially failing to detect leakage of soot past a defective filter into the exhaust flow, and adversely affecting emissions quality. Also, degradation of the filter (e.g., due to high soot leakage) may not be detected. In addition, by discarding a large amount of data, it may become difficult to meet the requirement of completing on-board diagnostics and meeting a target completion ratio within a given drive cycle.
The inventors herein have identified an approach by which the issues described above may be at least partly addressed. One example method includes collecting exhaust soot sensor data during engine operation while sensor noise is lower than a threshold; fitting a time-based curve to the collected data; predicting a sensor response time based on the curve fit; and in response to the curve fit being higher than a threshold, regenerating the soot sensor independent of a soot load of the sensor. In this way, a completion ratio of PM sensor diagnostics may be improved. Also, by using a predicted sensor output, soot concentration and/or soot flux in the exhaust may be estimated.
As an example, electric current signals corresponding to soot accumulation on a particulate matter (PM) sensor are collected over a period of time. In case of noisy PM sensor current signals (that is, on occurrence of a larger than threshold change in signal strength), the accumulated data is not used for determining an actual soot response time. The response time for regenerating the PM sensor (when soot load accumulated on the sensor reaches a threshold), may be predicted from at least a part of the accumulated signal. The actual response time may correspond to a duration of time elapsed between the end of one regeneration event and the start of an immediately subsequent regeneration event of the PM sensor (with no other regeneration event in between). As such, during steady-state driving conditions, the PM sensor signal may be less noisy, and the propensity for sensor noise may be higher during vehicle transients. Therefore, at least a portion of the total signal accumulated during steady-state conditions may be used for prediction of a response time of the sensor. As such, the prediction may be performed even before the accumulated signal reaches a pre-determined regeneration threshold and the sensor concentration measurements may be made early. A polynomial (quadratic) equation may be used to fit a plot generated from the data accumulated during the steady-state conditions. The response time may be predicted by extrapolating the curve fitted to the accumulation plot even before the actual signal reaches the threshold value. In addition, the linear term of the quadratic fit may be used to estimate the soot concentration on the PM sensor, which is also used to predict the time required (response time) for the soot level to reach the threshold value. The quality of the quadratic fit may be estimated by comparing the coefficient of determination (R2) of the plot to a threshold, and if the R2 value is higher than the threshold (that is, the fit is sufficiently reliable), sensor response time may be predicted by extrapolating the quadratic fit to the accumulation plot and stored. The predicted response time may be used to update the average response time of the PM sensor. Once sufficient data has been accumulated to enable a reliable prediction of response time, the PM sensor may be immediately regenerated and collection of a new dataset may be restarted. In particular, the sensor may be regenerated independent of the actual and/or predicted response time. If the R2 value is lower than the threshold (i.e. the fit is unreliable), and if the response time is very long or very short, the dataset may be discarded. The PM sensor may then be regenerated and reset to start another round of accumulation at a pre-determined response time. The predetermined response time may be based on the average response time, or based on a duration elapsed since a last regeneration of the sensor.
In this way, by relying on signal accumulated during conditions when sensor noise is lower, such as during steady-state conditions, PM sensor soot concentration may be calculated and regeneration can be scheduled even if the overall sensor signal (e.g., over a drive cycle) is noisy. By predicting the response time of a PM sensor by applying a quadratic fit to a plot generated from soot sensor data accumulated during steady-state conditions, the accuracy of the response time used for PM sensor measurements may be improved. By using a larger portion of the accumulated signal for response time prediction (and discarding a smaller portion), diagnostics may be completed within a drive cycle without reducing an accuracy in the estimation of the response time. By predicting response time and regenerating the PM sensor once sufficient data for enabling a reliable prediction is accumulated, a new dataset collection may commence without having to wait for the actual and/or predicted response time. As a result, a larger number of sensor response time signals may be collected per drive cycle, improving the completion ratio for the sensor. The technical effect of using a quadratic fit to the accumulation plot is that soot accumulation may also be estimated from the linear term of the fitted data. By estimating soot load on a sensor from the fit to soot accumulation plot using both techniques (that is, by extrapolating the quadratic fit to the accumulation plot and by using the linear term of the same fit), it may be possible to improve the accuracy of the average signal and thus the accuracy of the soot concentration measurement may be improved. For example, the response time learned via the first approach may be confirmed using the response time learned via the second approach. Also, a more accurate predicted response time may be used for sensor soot concentration measurement in place of an actual response time which may be not be accurate for the given drive cycle. By using a larger proportion of the accumulated signal for response time prediction, the likelihood of completing PM concentration measurement at least once within an emission test cycle (such as a federal test procedure cycle) is increased, improving engine emissions compliance. It will be appreciated that the method of predicting a sensor response time using a quadratic fit to a part of a signal accumulated at the sensor may be similarly utilized for a plurality of different sensors present in the vehicle.
It should be understood that the summary above is provided to introduce in simplified form a selection of concepts that are further described in the detailed description. It is not meant to identify key or essential features of the claimed subject matter, the scope of which is defined uniquely by the claims that follow the detailed description. Furthermore, the claimed subject matter is not limited to implementations that solve any disadvantages noted above or in any part of this disclosure.